The long term objectives of this proposal are to develop a system to monitor patients with pre-leukemic conditions like myelodysplastic syndrome (MDS) and myeloid proliferative neoplasms (MPN) for early detection of leukemic transition. This general system is stimulation of unfractionated bone marrow aspirates with cytokines and measuring the fine kinetics of modified epitopes on signaling proteins by immunofluorescence flow cytometry. Leukemia is an evolutionary process that works by clonal selection. Cytometry is a measurement sys- tem that works at the level of single cells, therefore, the specificity of detection and signal to noise ratio can be very high. In addition, cytometry is an established clinical tool used for diagnosis of hematopoietic malignancies based on measuring the levels of differentiation antigens. One model for the genesis of acute myeloid leukemia (AML) is that at least two mutations are leukemogenic: 1) in a transcription factor that alters differentiation, and 2) in a signaling pathway protein that affects cell proliferation and/or apoptosis. A significant component of cell signaling involves phosphorylation/de-phosphorylation cycles on pathway proteins, essentially from membrane surfaces to the genome, and between pathways (networks). We have developed the ability to measure cell signaling in committed myeloid precursor cells in unfractionated bone marrow by flow cytometry. Published results on normal, healthy volunteers demonstrates remarkable uniformity of response across age and gender, and published results on 4 (Jacobberger lab) and 14 (Goolsby lab) leukemias demonstrates clear, robust detection of abnormal signaling in eight pathways (Kit?Erk; ?Akt; ?S6; ?Stat5, and Flt3?Erk; ?Akt; ?S6; ?Stat5) that demonstrate classifiable complexity. Thus, we propose that cell signaling can be used as a biomarker to detect leukemic cells with high fidelity. Additionally, since the enzymes of these pathways are focus of targeted therapy, this approach provides information with therapeutic implications. Because a small fraction of abnormal cells can be detected by this approach, this should work well for early detection. Current diagnosis, therapeutic choices, and selection for clinical trials depend to some degree on genetic analysis, and in the future, this dependence will be greater. The signaling patterns, identified by our approach, will associate with specific mutations in signaling protein genes. Thus, cell signaling may provide rapid genetic inferences. To test this idea, we propose to correlate phenotype (signaling) and genotype, determined by high throughput sequencing. Our specific aims are 1) to measure signaling for 2 ligands (Stem cell factor and Flt3-ligand) and 5 endpoints (Erk, Akt, S6, Stat3, and Stat5) on committed myeloid precursor cells in 60 healthy human donors to define the normal ranges for each component of the signal analysis and determine any age or gender effects; 2) to measure signaling in 75 MDS and 75 AML patient blast cells to test the hypothesis that signaling can be classified by patterns and determine any age or gender effects; 3) to sequence 182 gene exons that may should impact on the signaling patterns for 10 MDS and 10 AML patients to demonstrate the feasibility of this approach for associating phenotype to genotype.